Clinical Decision Support for Unsolicited Genomic Results

主动提供的基因组结果的临床决策支持

• 批准号: 10318291
• 负责人: CASEY OVERBY TAYLOR
• 金额: $ 7.39万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10318291
• 关键词: Address; Adopted; Adoption; Area; Award; Clinical; Committee Members; Custom; Data; Diagnosis; Disease; Ensure; Feedback; Focus Groups; Future; Genomic medicine; Genomics; Goals; Health; Health Personnel; Health system; Healthcare; Individual; Infrastructure; Institution; Institutional Policy; Learning; Modeling; Motion; National Human Genome Research Institute; Outcome; Patients; Persons; Pharmacy and Therapeutics Committee; Prevention; Process; Recommendation; Research; Research Methodology; Risk; Role; Science; Structure; Surveys; System; Test Result; Testing; Time; Time and Motion Studies; Vision; Work; adverse drug reaction; base; clinical care; clinical decision support; computerized tools; dashboard; design; evidence base; genetic makeup; genomic data; health care settings; implementation science; improved; innovation; interest; meetings; preference; programs; provider adoption; research study; social; usability

PROJECT SUMMARY As healthy individuals increasingly can receive genomic testing results that indicate their risk for poor outcomes (e.g. diseases or adverse drug reactions), healthcare providers will need to ensure that the results are handled prudently, by addressing the receipt of the results, the workflow challenges, and liability issues. Given that clinical genomic tests can be initiated outside of the clinical setting (e.g., in a research study), from the clinician’s perspective, they can be characterized as unsolicited genomic results (UGR). Clinical decision support (CDS) has great potential to ease the adoption of UGR by providing clinicians with recommendations and patient-related information presented at particular times to enhance clinical care. Deploying CDS for UGR in a healthcare setting in a scalable way, however, will depend on our capacity to leverage local institutional policy and oversight structures to approve of CDS guidance and strategies for UGR. The specific objective of this research program is to develop and evaluate the Evidence-based Decision support Implementation over Time (EDIT) model for prioritizing and revising deployed CDS for UGR. The EDIT model will empower local oversight committees such as Pharmacy & Therapeutics committees to have a role in the CDS review and deployment processes within existing institutional social systems using accepted organizational processes. The direct benefits of this work will be an EDIT dashboard that can be used by oversight committees to prioritize new and to revise deployed CDS, and infrastructure to close the loop of the learning health system by transferring CDS revisions approved by oversight committee members into deployed CDS for UGR. EDIT model implementation will be informed by mixed methods research strategies: Strategy 1, we will conduct focus groups with oversight committee members in order to understand current roles, tasks and goals of the committee, as well as to capture opinions about the best processes to prioritize, review and approve of new and revised CDS for UGR as part of committee meeting activities. Research Strategy 2, we will conduct a survey study with patients to assess preferences for the return of UGR with CDS and usability studies with oversight committee members to gather feedback on the EDIT dashboard design. Strategy 3, we will conduct time-motion observations of local oversight committee meetings prior to and after deploying the EDIT model in order to plan a future, multi-institution, time- motion study with statistical power to detect differences between oversight committees that use the EDIT dashboard and those that do not. The hypothesis is that time spent prioritizing new and revised CDS will be shorter with use of the EDIT dashboard. Overall, the EDIT model establishes processes that lower barriers to implementing robust genomic medicine programs that can be followed by others. The Genomic Innovator Award will enable me to study, in team-science projects, how the EDIT model can accelerate the institutional review and approval process of CDS for UGR. The broader impact of this work is being able to study rate of UGR adoption by healthcare providers for deployed CDS for UGR.

项目摘要 随着健康个体越来越多地收到基因组测试结果，表明他们出现不良结果的风险 (e.g.疾病或药物不良反应），医疗保健提供者将需要确保处理结果 审慎地处理结果的接收、工作流程的挑战和责任问题。鉴于临床 基因组测试可以在临床环境之外开始（例如，在一项研究中），从临床医生的 从这个角度来看，它们可以被表征为非请求的基因组结果（UGR）。临床决策支持（CDS） 通过为临床医生提供建议和患者相关的信息， 在特定时间提供的信息，以加强临床护理。在医疗保健环境中为UGR部署CDS 但是，以可扩展方式，将取决于我们利用当地机构政策和监督的能力 批准CDS指导和UGR战略的结构。本研究计划的具体目标 开发和评估基于证据的决策支持随时间推移的实施（EDIT）模型 为UGR确定优先级并修订已部署的CDS。EDIT模式将授权地方监督委员会 如药学和治疗委员会在CDS审查和部署过程中发挥作用 在现有的社会制度中，使用公认的组织过程。这样做的直接好处是 工作将是一个编辑仪表板，可用于监督委员会优先考虑新的和修改 部署CDS，并通过转移CDS修订版来关闭学习健康系统的循环 经监督委员会成员批准，纳入UGR部署的CDS。EDIT模型的实施将 通过混合方法研究策略告知：策略1，我们将进行重点小组与监督 委员会成员，以了解委员会目前的作用，任务和目标，以及捕捉 关于优先考虑、审查和批准UGR新的和修订的CDS的最佳流程的意见， 委员会会议活动。研究策略二，我们会对病人进行调查研究， 与监督委员会成员一起收集的UGR与CDS和可用性研究的返回偏好 关于EDIT仪表板设计的反馈。策略3，我们将对当地监管进行时间运动观察 在部署EDIT模型之前和之后召开委员会会议，以规划未来的多机构时间- 具有统计能力的动议研究，以检测使用EDIT的监督委员会之间的差异 dashboard和那些没有的。我们的假设是，优先考虑新的和修订的CDS所花费的时间将 通过使用EDIT仪表板缩短。总的来说，EDIT模型建立了降低障碍的流程， 实施强有力的基因组医学计划，其他人可以效仿。基因组创新奖 这将使我能够在团队科学项目中研究EDIT模型如何加速机构审查 和UGR CDS的审批流程。这项工作的更广泛的影响是能够研究UGR率 医疗保健提供商采用已部署的UGR CDS。